This application relates to a systems and methods for trending issue identification in text streams. In one embodiment, a method for improving resolution of a trending issue identified in a set of text streams includes presenting a user interface of an application that is being executed by a computing device. The method also includes receiving a notification including the trending issue that has been identified in the set of text streams based at least in part on textual analysis performed on the set of text streams, and presenting the trending issue on the user interface of the application to enable an action to be performed to resolve the trending issue.
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8. The non-transitory computer readable storage medium of claim 1, wherein each of the plurality of text streams are included in a respective electronic message, a respective transcription, a respective chat history, a respective social media post, or a respective review.
This invention relates to processing and analyzing text data from various digital sources. The problem addressed is the need to efficiently extract and analyze meaningful information from diverse text streams, such as electronic messages, transcriptions, chat histories, social media posts, and reviews. The solution involves a computer-readable storage medium containing instructions for processing these text streams to identify and categorize relevant content. The system processes multiple text streams, each originating from different sources like emails, transcribed audio, chat logs, social media updates, or user reviews. The instructions enable the system to parse, filter, and analyze the text data to extract key information, such as sentiment, topics, or entities. The analysis may involve natural language processing (NLP) techniques to interpret the context and meaning of the text. The processed data can then be used for applications like customer feedback analysis, content moderation, or automated response generation. The invention ensures that text streams from various sources are handled uniformly, allowing for consistent and scalable analysis. By integrating multiple text sources, the system provides a comprehensive view of the data, improving decision-making and automation in digital communication and content management. The solution is particularly useful in environments where large volumes of text data are generated across different platforms.
16. The method of claim 9, wherein each of the plurality of text streams are included in a respective electronic message, a respective transcription, a respective chat history, a respective social media post, or a respective review.
This invention relates to processing and analyzing multiple text streams from various digital sources to extract and organize information. The method involves receiving a plurality of text streams, where each text stream is embedded within a different type of digital content, such as electronic messages, transcriptions, chat histories, social media posts, or reviews. The text streams are processed to identify and extract relevant information, which is then organized into a structured format for further analysis or use. The method may include filtering, categorizing, or summarizing the extracted information based on predefined criteria. The goal is to efficiently consolidate and analyze text data from diverse sources to improve information retrieval, decision-making, or content management in digital environments. The invention addresses challenges in handling unstructured or semi-structured text data from multiple sources, ensuring that relevant information is accurately identified and organized for practical applications.
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May 29, 2019
December 6, 2022
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